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为何某些重新利用的药物不太可能成为治疗新冠病毒感染的有效抗病毒药物。

Why Certain Repurposed Drugs Are Unlikely to Be Effective Antivirals to Treat SARS-CoV-2 Infections.

作者信息

Hurwitz Selwyn J, De Ramyani, LeCher Julia C, Downs-Bowen Jessica A, Goh Shu Ling, Zandi Keivan, McBrayer Tamara, Amblard Franck, Patel Dharmeshkumar, Kohler James J, Bhasin Manoj, Dobosh Brian S, Sukhatme Vikas, Tirouvanziam Rabindra M, Schinazi Raymond F

机构信息

Center for ViroScience and Cure, Laboratory of Biochemical Pharmacology, Department of Pediatrics, Emory University School of Medicine and Children's Healthcare of Atlanta, 1760 Haygood Drive, Atlanta, GA 30322, USA.

Center for Cystic Fibrosis & Airways Disease Research, Division of Pulmonary, Allergy & Immunology, Cystic Fibrosis and Sleep, Emory University and Children's Healthcare of Atlanta, 2015 Uppergate Drive, Atlanta, GA 30322, USA.

出版信息

Viruses. 2024 Apr 22;16(4):651. doi: 10.3390/v16040651.

Abstract

Most repurposed drugs have proved ineffective for treating COVID-19. We evaluated median effective and toxic concentrations (EC, CC) of 49 drugs, mostly from previous clinical trials, in Vero cells. Ratios of reported unbound peak plasma concentrations, (C)/EC, were used to predict the potential in vivo efficacy. The 20 drugs with the highest ratios were retested in human Calu-3 and Caco-2 cells, and their CC was determined in an expanded panel of cell lines. Many of the 20 drugs with the highest ratios were inactive in human Calu-3 and Caco-2 cells. Antivirals effective in controlled clinical trials had unbound C/EC ≥ 6.8 in Calu-3 or Caco-2 cells. EC of nucleoside analogs were cell dependent. This approach and earlier availability of more relevant cultures could have reduced the number of unwarranted clinical trials.

摘要

大多数重新利用的药物已被证明对治疗新冠病毒无效。我们评估了49种药物(大多来自先前的临床试验)在Vero细胞中的半数有效浓度和毒性浓度(EC、CC)。使用报告的非结合血浆峰值浓度(C)与EC的比值来预测体内潜在疗效。对比值最高的20种药物在人Calu-3和Caco-2细胞中进行了重新测试,并在一组扩展的细胞系中测定了它们的CC。比值最高的20种药物中有许多在人Calu-3和Caco-2细胞中无活性。在对照临床试验中有效的抗病毒药物在Calu-3或Caco-2细胞中的非结合C/EC≥6.8。核苷类似物的EC具有细胞依赖性。这种方法以及更早获得更相关的培养物可能会减少不必要的临床试验数量。

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